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AI Watermarking is embedding a machine-detectable marker in AI-generated content so it can later be identified as synthetic.
AI Watermarking, embedding a machine-detectable marker in AI-generated content so it can later be identified as synthetic.
Watermarking helps address the provenance problem, telling whether content was produced by AI. The EU AI Act's Article 50(2) requires providers of generative systems to mark their synthetic output in a machine-readable, detectable way; the Digital Omnibus on AI, published in the Official Journal on 24 July 2026 and in force from 27 July 2026, gave this obligation a grace period to 2 December 2026 for systems already on the market before 2 August 2026, making it one of the nearest-term AI Act deadlines. Open standards such as C2PA aim to carry provenance signals across platforms. Watermarks can be removed or degraded, so they are a partial control rather than a guarantee.
Source: EU AI Act, Article 50(2); C2PA Content Provenance
Watermarking helps address the provenance problem, telling whether content was produced by AI. The EU AI Act's Article 50(2) requires providers of generative systems to mark their synthetic output in a machine-readable, detectable way; the Digital Omnibus on AI, published in the Official Journal on 24 July 2026 and in force from 27 July 2026, gave this obligation a grace period to 2 December 2026 for systems already on the market before 2 August 2026, making it one of the nearest-term AI Act deadlines. Open standards such as C2PA aim to carry provenance signals across platforms. Watermarks can be removed or degraded, so they are a partial control rather than a guarantee.
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